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Bielik 11B V3.0 Instruct — Hardware Requirements & GPU Compatibility

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Bielik 11B V3.0 Instruct is a 11.2B-parameter open language model from speakleash. At BF16 it needs about 24.57 GB of VRAM — see which GPUs and Macs can run it below.

11.2B params · denseApache 2.0Nov 20259.6K downloads116 likes36.0K quant downloads

Your hardware

Verdicts below are for the reference RTX 4090. Set yours to personalise the page.

Detection reads your browser's GPU name with no data sent anywhere.

Doesn't fit a 24 GB GPU

Smallest consumer fit → Snapdragon X Elite Copilot+ PC · BF16 · 27.4 GB · ~4 tok/s

Macs from 32 GB (BF16 · ~11 tok/s)

Apache 2.0

Not set up for it?

Reference GPU · RTX 4090 24 GB

Estimates, ±20% · how we estimate

Run Bielik 11B V3.0 Instruct

One recommended way. Every other method, OS and quant is in the step-by-step guide.

Other ways

each opens step-by-step

Run in cloud

Fits on RTX A6000 (48 GB) (20 GB headroom) · BF16

Generation speed: ~20 tok/s; generation speed
Cost per 1M output tokens: $4.52; per 1M output tokens

Deployon RunPodBest optionfrom $0.33/hr

Compare GPUs →

Run Bielik 11B V3.0 Instruct

27.4 GB VRAM at 16K context · needs offload on the RTX 4090 (3.4 GB short)

Ollama is not available

No GGUF repository is listed for this model.

Linux only.

Install vLLM
Linux only; on Windows run it inside WSL2. NVIDIA GPU shown; AMD ROCm, Intel and CPU builds have their own install pages.
$uv venv --python 3.12 --seed
$source .venv/bin/activate
$uv pip install vllm --torch-backend=auto
vLLM installation ↗
Serve the model
OpenAI-compatible API at http://localhost:8000/v1.
$vllm serve speakleash/Bielik-11B-v3.0-Instruct --max-model-len 16384
Runs the original weights, not the BF16 GGUF; needs ~25 GB of GPU memory.

Rent GPUs hourly to run BF16 right there. Pricing comes from partner marketplaces and varies.

Available GPU rentals for BF16, prioritized by value
GPU	Speed	$/1M tokens	Rent
RTX A6000 (48 GB)CheapestCheapest20 GB free	~20 tok/s	$4.52	Deploy on RunPodfrom $0.33/hr (opens in new tab)	48 GB · 20 GB free · ~20 tok/s · $4.52 / 1M tokens
A40 (48 GB)20 GB free	~18 tok/s	$5.28	Deploy on RunPodfrom $0.35/hr (opens in new tab)	48 GB · 20 GB free · ~18 tok/s · $5.28 / 1M tokens
RTX A6000 (48 GB)20 GB free	~20 tok/s	$5.52	Deploy on Vast.aifrom $0.40/hr (opens in new tab)	48 GB · 20 GB free · ~20 tok/s · $5.52 / 1M tokens
A40 (48 GB)20 GB free	~18 tok/s	$8.09	Deploy on Vast.aifrom $0.54/hr (opens in new tab)	48 GB · 20 GB free · ~18 tok/s · $8.09 / 1M tokens
RTX 6000 Ada (48 GB)20 GB free	~25 tok/s	$7.02	Deploy on Vast.aifrom $0.64/hr (opens in new tab)	48 GB · 20 GB free · ~25 tok/s · $7.02 / 1M tokens
A100 40GB12 GB free	~41 tok/s	$4.97	Deploy on Vast.aifrom $0.73/hr (opens in new tab)	12 GB free · ~41 tok/s · $4.97 / 1M tokens
RTX 6000 Ada (48 GB)20 GB free	~25 tok/s	$8.09	Deploy on RunPodfrom $0.74/hr (opens in new tab)	48 GB · 20 GB free · ~25 tok/s · $8.09 / 1M tokens
L40S (48 GB)20 GB free	~23 tok/s	$9.58	Deploy on RunPodfrom $0.79/hr (opens in new tab)	48 GB · 20 GB free · ~23 tok/s · $9.58 / 1M tokens

Compare GPUs →

How Much VRAM Does Bielik 11B V3.0 Instruct Need?

Select a quantization level; the listed hardware adheres to it.

Quantization	VRAM	+32K	+128K	File	Quality	On RTX 4090 (reference)
	24.6 GB	30.6 GB	49.9 GB	~22.3 GB	16-bit · bfloat — Brain floating point 16 — preferred for training	Does not fit: needs 27.4 GB

est.calculated, no published file yet

Selected BF16

Brain floating point 16

27.4GBat 16K context

Weights: 23.9 GB
KV cache: 3.2 GB
Overhead: 0.3 GB

Doesn't fit RTX 4090 (reference) · needs 3.4 GB more

≥30 tok/s needs ≥1.13 TB/s · RTX 5090 ~47

Or rent RTX A6000 from $0.33/hr.

Which Hardware Can Run Bielik 11B V3.0 Instruct?

BF16 · 24.6 GB

Bielik 11B V3.0 Instruct (BF16) requires 24.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 32+ GB is recommended. 1 GPU can run it, including NVIDIA GeForce RTX 5090. 98 devices with unified memory can run Bielik 11B V3.0 Instruct, including Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB), Mac Studio M5 Max (36 GB).

By VRAM tier · typical GPUs and Macs at BF16

Typical hardwareQuantVRAMtok/sContext that fits

8–16 GB · RTX 4060, RTX 3060 12GB, RTX 5060 Ti 16GBDoesn't fit — smallest quant needs 27.4 GB8 GB tier →12 GB tier →16 GB tier →

24 GB · RTX 4090referenceDoesn't fit — smallest quant needs 27.4 GB24 GB tier →

Mac 32 GB · Mac Mini M4BF16 · 27.4 GB · ~3 tok/s · 16K27.4~316KMacs →

Mac 64 GB · Mac Studio M4 MaxBF16 · 27.4 GB · ~16 tok/s · 32K27.4~1632KMacs →

Alternatives to Bielik 11B V3.0 Instruct

Similar models

5tok/s on RTX 4090

Model	Score	VRAM	tok/s	Why it is similar
Gemma 4 12BGoogle	—	9 GB	~80	same size
Qwen2.5 Omni 7BAlibaba	—	9.9 GB	~93	same size
Llama 3.2 11B Vision InstructMeta	—	9.8 GB	~93	same size
Falcon 11BTII UAE	—	8.5 GB	~89	same size
SOLAR 10.7B Instruct v1.0Upstage	—	7.5 GB	~92	same size

Specifications

Publisher: speakleash
Parameters: 11.2B
Release Date: 2025-11-07
License: Apache 2.0

Resources

Hugging Face model card (opens in a new tab)

Frequently Asked Questions

How much VRAM does Bielik 11B V3.0 Instruct need?

Bielik 11B V3.0 Instruct requires 24.6 GB of VRAM at BF16.

VRAM = Weights + KV Cache + Overhead

Weights = 11.2B × 16 bits ÷ 8 = 22.3 GB

KV Cache + Overhead ≈ 2.3 GB (at 2K context + ~0.3 GB framework)

Fit ratings and hardware model lists check this model with room for a 16K-token context, which needs a little more memory.

VRAM usage by quantization

BF16

24.6 GB

Learn more about VRAM estimation →

Can I run Bielik 11B V3.0 Instruct on a Mac?

Yes — Mac Studio M1 Max (32 GB) and 84 other Macs can run Bielik 11B V3.0 Instruct. Apple Silicon uses unified memory, so the model shares RAM with the system. At BF16 you need at least 24.6 GB of usable unified memory (RAM minus macOS overhead).

Can I run Bielik 11B V3.0 Instruct locally?

Yes — Bielik 11B V3.0 Instruct can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is Bielik 11B V3.0 Instruct?

At BF16, Bielik 11B V3.0 Instruct can reach ~195 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.

tok/s = (bandwidth GB/s ÷ model GB) × efficiency

Example: NVIDIA B200 → 8000 ÷ 24.57 × 0.65 = ~212 tok/s

Estimated speed at BF16 (24.6 GB)

NVIDIA B200

~212 tok/s

NVIDIA B300

~212 tok/s

AMD Instinct MI350X

~195 tok/s

Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.

Learn more about tok/s estimation →

What's the download size of Bielik 11B V3.0 Instruct?

At BF16, the download is about 22.34 GB.

Which GPUs can run Bielik 11B V3.0 Instruct?

1 consumer GPU can run Bielik 11B V3.0 Instruct at BF16. Top options include NVIDIA GeForce RTX 5090.

Which devices can run Bielik 11B V3.0 Instruct?

98 devices with unified memory can run Bielik 11B V3.0 Instruct at BF16 (24.6 GB), including ASUS Ascent GX10, Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (Ryzen AI Max+ 395, 128 GB), GMKtec EVO-X2 (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.

Bielik 11B V3.0 Instruct — Hardware Requirements & GPU Compatibility

Doesn't fit a 24 GB GPU

Run Bielik 11B V3.0 Instruct

Recommended

Other ways

Run in cloud

Run Bielik 11B V3.0 Instruct

Install vLLM

Serve the model

All sources

How Much VRAM Does Bielik 11B V3.0 Instruct Need?

Selected BF16

Which Hardware Can Run Bielik 11B V3.0 Instruct?

Alternatives to Bielik 11B V3.0 Instruct

Similar models

Specifications

Resources

Frequently Asked Questions

Run Bielik 11B V3.0 Instruct

Install vLLM

Serve the model

All sources